Modern mass spectrometry (MS) systems allow scientists to routinely determine the quantitative composition of cells or tissue samples. However, different analysis software packages often produce different results from the same raw data. An international team of researchers led by Stefan Tenzer at the Mainz University Medical Center in Germany has now addressed this problem.

Within the framework of an international collaboration with leading laboratories worldwide, the team has compared and modified various analysis software packages to ensure that the different software solutions produce consistent results. A wide range of laboratories around the world are already benefiting from this work, allowing researchers to analyze or compare the results of quantitative proteomics assays in a standardized way. This is crucial for detecting certain organic diseases, such as cancer, at an early stage. Tenzer and his team recently reported their work in Nature Biotechnology.

When doctors want to find the cause of a particular illness, they have to take samples of cells or bodily fluids. These samples are then analyzed by modern ‘omics techniques that can reproducibly quantify thousands of proteins across large numbers of samples in order to identify novel biomarkers for diseases. The analysis of these highly complex datasets critically depends on specialized software packages. Unfortunately, different software packages sometimes generate different results from the same raw data, thus complicating the analysis.

This is the problem that Tenzer and his team from the Institute of Immunology at the Mainz University Medical Center set out to resolve. "We wanted to find a way of optimally comparing samples, even when different analysis software sometimes produces deviating results," explained Tenzer.

For this latest project, Tenzer conducted MS analyses on two defined samples with precisely defined ratios of constituents. The bioinformatics specialists in Tenzer's team, Pedro Navarro and Jörg Kuharev, developed a specialist piece of software, termed LFQbench, which allowed the team to study the differences between the various analysis programs in detail.

"Using LFQbench, we were able to show that the results delivered by the various programs differed significantly," explained Navarro. "This finding alone has significant impact for the scientific community. But we have taken the project a step further: Our close collaboration with the developers of the individual programs enabled them to modify and improve their analysis packages so that they now produce highly convergent results," added Tenzer. This broadens the scope of applications of the MS technique known as quantitative proteomics. "This means that in the future, mass spectrometry will be able to provide even more benefits both in basic research and as a potential diagnostic tool," Tenzer said.

"This development represents a breakthrough for mass spectrometry-based quantitative proteomics and makes this method increasingly important as a standard procedure for use in the diagnosis of various disorders, such as cancer or allergies," emphasized Ulrich Förstermann, chief scientific officer of the Mainz University Medical Center. "I am particularly proud that our researchers are delivering applied research with such significant impact."

"This success demonstrates the necessity of combining different areas of expertise in technology platforms at the University Medical Center. Without central support, it is nowadays almost impossible to accomplish achievements of this kind," said Hansjörg Schild, director of the Institute of Immunology and coordinator of the Research Center for Immunotherapy.

Over recent years, Tenzer and his team in Mainz have developed several improvements to the techniques used for MS-based quantitative proteomics. "The years of work within the technology platform, especially in international joint projects, have paid off in terms of this quantum leap forward in mass spectrometry-based quantitative proteomics," concluded Tenzer.